Please use this identifier to cite or link to this item: https://ir.iimcal.ac.in:8443/jspui/handle/123456789/1344
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dc.contributor.authorMateen, Arqum
dc.contributor.authorChatterjee, Ashis Kumar
dc.contributor.authorMitra, Subrata
dc.date.accessioned2021-08-26T06:05:26Z-
dc.date.available2021-08-26T06:05:26Z-
dc.date.issued2015
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84911890034&doi=10.1016%2fj.cie.2014.10.028&partnerID=40&md5=218abfafd9b851a028a27d7ad4e87e34
dc.identifier.urihttps://ir.iimcal.ac.in:8443/jspui/handle/123456789/1344-
dc.descriptionMateen, Arqum, Indian Institute of Management Kozhikode, IIMK Campus P.O., Kozhikode, 673570, India; Chatterjee, Ashis Kumar, Indian Institute of Management Calcutta, Joka Diamond Harbor Road, Kolkata, 700104, India; Mitra, Subrata, Indian Institute of Management Calcutta, Joka Diamond Harbor Road, Kolkata, 700104, India
dc.descriptionISSN/ISBN - 03608352
dc.descriptionpp.95-102
dc.descriptionDOI - 10.1016/j.cie.2014.10.028
dc.description.abstractThis paper discusses how a vendor and multiple retailers interact in a vendor managed inventory (VMI) system under stochastic demand. It is assumed that the vendor replenishes all the retailers at the same time. The vendor replenishment cycle is taken to be an integer multiple of the retailer replenishment cycle. In case of a shortage at the vendor, the available stock is allocated to the retailers on the basis of equal stock out probability. Approximate expressions for minimizing the expected total cost for the VMI system have been developed. Various levers affecting the performance of the system have been analyzed. The validity of the approximate model has been tested through simulation. � 2014 Elsevier Ltd.
dc.publisherSCOPUS
dc.publisherComputers and Industrial Engineering
dc.publisherElsevier Ltd
dc.relation.ispartofseries79
dc.subjectSimulation
dc.subjectStochastic demand
dc.subjectSupply chain management
dc.subjectVendor managed inventory
dc.titleVMI for single-vendor multi-retailer supply chains under stochastic demand
dc.typeArticle
Appears in Collections:Operations Management

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